Paid Masters Thesis: Model Predictive Control of
vor 6 Monaten
Welcome to the sustainable world of BEST
BEST - Bioenergy and Sustainable Technologies GmbH is the competence center in Austria that conducts pre-competitive industry-related research in the field of bioenergy and biobased economy.
At BEST we work as a team to actively shape the transition to a sustainable and climate friendly bioeconomy.
Your talent and your passion for research and science are explicitly needed with us. Collaborate with us on interesting and promising tasks and develop your scientific creativity. Join us on our approach to a more environmentally and climate friendly future
Team player? Enthusiastic? Open-minded? Then you are exactly right at BEST.
Tasks
Hydrogen technologies (e.g. electrolyzers, gas tanks, fuel cells,) have become increasingly important in recent years.
However, optimal control of such systems comes with a challenge, as the explicit consideration of pressure and mass flow require non-linear models.
The goal of this thesis is to investigate and compare different modelling approaches, on the example of an H2-charging station, for use in a model predictive controller (MPC).
Objectives
- Investigation of different modelling approaches (linear, non-linear, integrator-model, physically-motivated,) for prediction of hydrogen production, demand and distribution
- Implementation of selected models for hydrogen technologies in Matlab/Python/Julia
- Implementation of an H2-charging station and evaluating the different modelling approaches for usability as MPC strategies
- OPTIONAL: Additional modelling of logistics/distribution constraints for the MPC
**Requirements**:
- Studies in digital, electrical, mechanical or information and computer engineering, etc.
- Basic knowledge of a programming language like MATLAB, Python or (ideally) Julia
- Basic knowledge of control engineering and optimization
- Study admission for an Austrian university, EU visa, residence permit
**Benefits**:
- Integration into a dedicated team with good support
- Flexible working arrangements
- Perspective of participation in follow-up projects after successful completion
- Financial compensation based on student staff salary scheme
- Remote work from home is possible
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